The present investigation is focused on the solution of a dynamic inverse problem which is concerned with the assessment of damage in large space structures by means of measured vibration data. This inverse problem has been presented as an optimization problem and has been solved through the use of the Conjugate Gradient method with the Adjoint Equation also called Variational Approach. When a high number of damage elements is to be individualized and these elements are also severely damaged, it is shown that the use of an additional method is necessary in order to provide a better initial guess for the conjugate gradient method. A stochastic method, represented by the Genetic Algorithm Method, has been chosen because it provides robust search in complex spaces and also reduces the chance of converging to local optima. The application of this hybrid approach showed that better results can be achieved, although the computational time for the application here analyzed could increase. The damage estimation has been evaluated using noiseless and noisy synthetic experimental data, and the reported results are concerned with a space truss structure.
Damage assessment of large space structures through the variational approach / Gasbarri, Paolo; L. D., Chiwiacowsky; H. F., De Campos Velho. - STAMPA. - 3:(2004), pp. 1834-1844. (Intervento presentato al convegno International Astronautical Federation - 55th International Astronautical Congress 2004 tenutosi a Vancouver nel 4 October 2004 through 8 October 2004).
Damage assessment of large space structures through the variational approach
GASBARRI, Paolo;
2004
Abstract
The present investigation is focused on the solution of a dynamic inverse problem which is concerned with the assessment of damage in large space structures by means of measured vibration data. This inverse problem has been presented as an optimization problem and has been solved through the use of the Conjugate Gradient method with the Adjoint Equation also called Variational Approach. When a high number of damage elements is to be individualized and these elements are also severely damaged, it is shown that the use of an additional method is necessary in order to provide a better initial guess for the conjugate gradient method. A stochastic method, represented by the Genetic Algorithm Method, has been chosen because it provides robust search in complex spaces and also reduces the chance of converging to local optima. The application of this hybrid approach showed that better results can be achieved, although the computational time for the application here analyzed could increase. The damage estimation has been evaluated using noiseless and noisy synthetic experimental data, and the reported results are concerned with a space truss structure.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.